The outlier analysis tutorial and templates use the box & whisker plot graph to analyze each data point and flag "High Outlier" and "Low Outlier" values based on the 1.5(IQR) Outlier Rule that is applied to the Interquartile Range (IQR) statistic of one or more columns of data:
High Outlier > 75th percentile + 1.5(IQR)
Low Outlier < 25th percentile - 1.5(IQR)
You can apply the 1.5(IQR) Statistical Outlier Formula to one or more columns of data. Sort the data from the highest to lowest value: identify the 75th percentile which is the value with 75% of the data values below it, and the 25th percentile which has 25% of the data values below it. The 75th percentile - the 25th percentile is the Interquartile Range (IQR) statistic. Then apply the above two IQR formulas above to your calculated IQR statistic to identify the "High Outlier" and "Low Outlier" values in your data. The output below is an example summary report generated by completing the 1.5(IQR) Outlier Analysis Tutorial that applies the 1.5(IQR) Outlier Analysis Rule.
Learn About 1.5(IQR) Outlier Analysis